If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Mercedes-Benz is giving drivers an even smarter luxury experience and adding some AI assistant power to its newest vehicles. All Mercedes-Benz models from 2016 and 2017 are now compatible with both Google Assistant and Amazon Alexa, taking the smart home experience out on the road. SEE ALSO: Lynk & Co's sedan concept boasts free internet The AI assistants will allow drivers to do things like remote start their car using a voice command from the comfort of their kitchen or adjust their smart home appliance settings from the driver's seat. You can check out the system in action in the demo below -- just don't get in the habit of leaving your iron and stove burning in your house, smart assistant or not. Connecting the systems is a bit complicated, though -- in order to set up either of the AI assistants, you'll need an active Mercedes me account and an active mbrace subscription.
Artificial Intelligence:: AI is the capability of a machine to imitate intelligent human behavior. BMW, Tesla, Google are using AI for self-driving cars. AI should be used to solve real world tough problems like climate modeling to disease analysis and betterment of humanity. Boosting and Bagging: it is the technique used to generate more accurate models by ensembling multiple models together Crisp-DM: is the cross industry standard process for data mining. It was developed by a consortium of companies like SPSS, Teradata, Daimler and NCR Corporation in 1997 to bring the order in developing analytics models.
A drone that can spot sharks and warn people has been developed by Australian researchers. The battery powered, unmanned drone uses an artificial intelligence technology to identify sharks and send out a safety warning through a megaphone. The drones will be used to patrol many main beaches in Australia from the summer of 2017 or 2018. The battery powered, unmanned drones uses an artificial intelligence technology to identify sharks and send out a safety warning through a megaphone. The drone works via real time analysis of overhead footage, and information can be relayed immediately to emergency services, beach lifeguards and beach users to help make safe decisions about getting into the water.
Planet, the satellite imaging company that operate the largest commercial Earth imaging constellation in existence, is hosting a new data science competition on the Kaggle platform, with the specific aim of developing machine learning techniques around forestry research. Planet will open up access to thousands of image'chips,' or blocks covering around 1 sauce kilometre, and will give away a total of $60,000 to participants who place in the top three when coming up with new methods for analyzing the data available in these images. Planet notes that each minute, we lose a portion of forest the size of approximately 48 football fields, which is a heck of a lot of forest. The hope is that by releasing this data and hosting this competition, Planet can encourage academics and researchers worldwide to apply advances in machine learning that have been put to great use in efforts like facial recognition and detect, to this pressing ecological problem. "We're putting together this competition as a way to get people excited about the kinds of data that Planet provides," explained Planet machine learning engineer Kat Scott in an interview.
Beyond all that, primary significance of course sits with the AI engine that underpins the interaction. Roughly half of the considerations listed above will not be resolved wholly satisfactorily until the AI can do the heavy lifting necessary to, for example, autonomously resolve an ambiguity in the stated input. This is starting to happen, for example, using Google Home (unlike with the Echo), it is possible (subject to the usual tally of hit'n' miss attempts) to ask for something, then ask a contextual follow-up, in what can legitimately be labelled a (basic) conversational interaction. See also: Voice recognition: has AI just beaten a human? The interesting thing for anyone observing the emergence of voice user interfaces in mass-market products, is the relationship between that form of interaction and the more conventional screen-based interactions. Screen-based interfaces are an abstraction in a way that voice interaction arguably is not. Yet the nascent nature of voice interaction still necessitates a screen for effective'long-form" interaction – by which we mean detailed immersion in complex content. For now, voice augments, rather than displaces the screen-based outcome: witness the regularity with which the Echo will resolve a query by sending some links to the Alexa app, a mode of behaviour also more than familiar to anyone persisting with Siri.
For anyone who's ever seen an early episode of Star Trek, recall Captain Kirk speaking to the "computer," even using that keyword to summon the computing power of the Starship Enterprise to answer a complex question requiring an expeditious answer. Ever since Gene Roddenberry introduced his sci-fi interpretation of the future, we've been chasing that dream, for as early as 1952, Bell Labs scientists introduced "Audrey," a system that recognized spoken numeric digits. Fast-forward from the days of Star Trek and Audrey, and researchers have turned the science fiction of a seamless voice interface into reality. Apple's Siri, Amazon's Alexa, Microsoft's Cortana and Google's voice assistant are all manifestations of decades worth of research. Thanks to this tech confluence, today's voice systems can understand the context of an entire conversation, even the personality of whom they are conversing with.
Amazon.com, Inc. 's AMZN Amazon Web Services (AWS) has made Amazon Lex, the machine learning technology behind Alexa, available to all customers. Amazon Lex algorithms facilitate natural language understanding, automatic speech recognition and text to speech. Amazon is now offering these technologies as a fully managed service. With Amazon Lex, developers can build conversational apps easily, which were otherwise extremely difficult to create as these involved complicated deep learning algorithms on enormous amount of data. Moreover, the integration of Amazon Lex with AWS Lambda (Amazon's event-driven, serverless computing platform) will enable developers to run serverless codes, apply business logic and fetch data from enterprise applications and AWS services like Amazon DynamoDB.
About 35 percent of healthcare organizations plan to leverage artificial intelligence within two years -- and more than half intend to do so within five. "If you look at those with plans to leverage AI in some way, shape or form, we're going to see significant growth," said Brendan FitzGerald, director of research at HIMSS Analytics. While only 4.7 percent of the 85 survey respondents are already using AI technologies, the future looks promising. Indeed, 10.6 percent plan to adopt them within 12 months, 23.5 percent indicated they will within two years and another 24.7 percent in three to five years. Participants ranked population health, clinical decision support, patient diagnosis and precision medicine, respectively, as the top places AI will have the most substantial initial impact.
Elon Musk has a new plan to protect humanity from artificial intelligence -- if you can't beat'em, join'em. In October 2014, Musk ignited a global discussion on the perils of artificial intelligence. Humans might be doomed if we make machines that are smarter than us, Musk warned. He called artificial intelligence our greatest existential threat. Now he is hoping to harness AI in a way that will benefit society.
SYRACUSE, N.Y.--It was a nightmare scenario: As thousands of Syracuse University basketball fans poured into town on February 1, 2014 for a big match against arch rival Duke, a water main break flooded Armory Square, surrounding the city's iconic 24-second shot clock monument. Days before the game, there were 11 other water main breaks around the city. Mayor Stephanie Miner was desperate for help to get a handle on the problem; on average, water lines in the city were breaking 332 times a year, nearly once every day. But she couldn't get the state to help foot the bill for the onerous costs of updating the city's underground infrastructure. She even tried to shame state officials with a "Hunger Games"-style ad campaign that showed her wading in thigh-high water wielding a wrench.